The engineering of IoT systems brings about various challenges due to the inherent complexities associated with such heterogeneous systems. In this paper, we propose a library of statechart templates, STL4IoT, for designing complex IoT systems. We have developed atomic statechart components modeling the heterogeneous aspects of IoT systems including sensors, actuators, physical entities, network, and controller. Base system units for smart systems have also been designed. A component for calculating power usage is available in the library. In addition, a smart hub template that controls interactions among multiple IoT systems and manages power consumption has also been proposed. The templates aim to facilitate the modeling and simulation of IoT systems. Our work is demonstrated with a smart home system consisting of a smart hub of lights, a smart microwave, a smart TV, and a smart fire alarm system. We have created a multi statechart with Itemis CREATE based on the proposed templates and components. A smart home simulator has been developed by generating controller code from the statechart and integrating it with a user interface.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11875881 | PMC |
http://dx.doi.org/10.1177/00375497241290369 | DOI Listing |
Sci Rep
March 2025
Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
The volume of confidential information transmitted over 5G networks has increased rapidly due to the widespread adoption of large machine-type communication and Internet of Things (IoT) devices. Secrecy outage probability (SOP) and strictly positive secrecy capacity (SPSC) parameters are crucial parameters used in evaluating the security of wireless systems, particularly in situations where maintaining secrecy is essential. Also, Non-orthogonal multiple access (NOMA) has the potential to improve the performance of wireless communication systems due to its higher spectral efficiency, improved fairness in resource allocation, and enhanced coverage and connectivity.
View Article and Find Full Text PDFSci Rep
March 2025
Department of Software Engineering, College of Engineering and Computer Science, University of Jeddah, Jeddah, Saudi Arabia.
The rapid growth of the Internet of Things (IoT) and its extensive use in many regions, such as smart homes, healthcare, and vehicles, have made IoT security increasingly critical. Ransomware is an advanced and adjustable threat influencing users globally, limiting admittance to their data or systems over models like file encryption or screen locking. Traditional ransomware detection methods frequently drop, deprived of the ability to combat these threats successfully.
View Article and Find Full Text PDFJ Imaging Inform Med
March 2025
Artificial Intelligence, Software, Information Systems Engineering Departments, AI and Robotics Institute, Near East University, Mersin10, Nicosia, Turkey.
Brain tumor is categorized as one of the most fatal form of cancer due to its location and difficulty in terms of diagnostics. Medical expert relies on two key approaches which include biopsy and MRI. However, these techniques have several setbacks which include the need of medical experts, inaccuracy, miss-diagnosis as a result of anxiety or workload which may lead to patient morbidity and mortality.
View Article and Find Full Text PDFPeerJ Comput Sci
January 2025
College of Physical Education, Luoyang Normal University, Henan, China.
In recent years, growth in technology has significantly impacted various industries, including sports, health, e-commerce, and agriculture. Among these industries, the sports sector is experiencing significant transformation, which needs support in accurately monitoring athlete predicting and performance injuries arising due to traditional methods' limitations. Keeping the above in mind, in this article, we present the Intelligent Sports Management System (ISMS) with the integration of wireless sensor networks (WSNs) and neural networks (NNs), which enhance athlete monitoring and injury prediction.
View Article and Find Full Text PDFPeerJ Comput Sci
February 2025
China Telecom Research Institute, Guangzhou, Guangdong Province, China.
Over the past two decades, sequential recommendation systems have garnered significant research interest, driven by their potential applications in personalized product recommendations. In this article, we seek to explicitly model an algorithm based on Internet of Things (IoT) data to predict the next cell reached by the user equipment (UE). This algorithm exploits UE embedding and cell embedding combining the visit time interval information, and uses sliding window sampling to process more UE trajectory data.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!